Abstrait

Implementation of Digital Signal Processing Algorithm in General Purpose Graphics Processing Unit (GPGPU)

Jagdamb Behari Srivastava, R.K. pandey, Jitendra Jain

In this paper, we have proposed sequential and parallel matrix and matrix-vector multiplication in compute unified device architecture (CUDA) libraries. We show the process of a class of algorithms parallelization which are used in digital signal processing. We present this approach on the instance of the Linear Convolution, Circular Convolution, and Least Mean Square (LMS) algorithm. We propose an approach which uses a general purpose graphics processor unit (GPGPU) technology. The accelerated version on GPU computed faster because it took less time compare to the MATLAB and sequential implementation.